6 citations · 12 across the 17 of their papers we have counts for
16 papers · 1 filter
Reinforcing Egocentric Spatial Perception in Multimodal Large Language Models via Ego Scene Augmentation
Chi Kit Wong, Ye Pan, Yuanhuiyi Lyu +6
Egocentric Visual Question Answering (VQA) has attracted widespread attention as an important task for enabling Multimodal Large Language Models (MLLMs) to interact with the real w…
Holo360D: A Large-Scale Real-World Dataset with Continuous Trajectories for Advancing Panoramic 3D Reconstruction and Beyond
Jing Ou, Zidong Cao, Yinrui Ren +6
While feed-forward 3D reconstruction models have advanced rapidly, they still exhibit degraded performance on panoramas due to spherical distortions. Moreover, existing panoramic 3…
SAP: Segment Any 4K Panorama
Lutao Jiang, Zidong Cao, Weikai Chen +14
Promptable instance segmentation is widely adopted in embodied and AR systems, yet the performance of foundation models trained on perspective imagery often degrades on 360° panora…
EventVGGT: Exploring Cross-Modal Distillation for Consistent Event-based Depth Estimation
Yinrui Ren, Jinjing Zhu, Kanghao Chen +8
Event cameras offer superior sensitivity to high-speed motion and extreme lighting, making event-based monocular depth estimation a promising approach for robust 3D perception in c…
A Survey of Representation Learning, Optimization Strategies, and Applications for Omnidirectional Vision
Hao Ai, Zidong Cao, Lin Wang
Omnidirectional image (ODI) data is captured with a field-of-view of 360x180, which is much wider than the pinhole cameras and captures richer surrounding environment details than…
PanDA: Towards Panoramic Depth Anything with Unlabeled Panoramas and Mobius Spatial Augmentation
Zidong Cao, Jinjing Zhu, Weiming Zhang +4
Recently, Depth Anything Models (DAMs) - a type of depth foundation models - have demonstrated impressive zero-shot capabilities across diverse perspective images. Despite its succ…